code: def test_sdml_supervised(self):
      seed = np.random.RandomState(1234)
      sdml = SDML_Supervised(
          n_constraints=1500,
          balance_param=1e-5,
          prior="identity",
          random_state=seed,
      )
      sdml.fit(self.X, self.y)
      res_1 = sdml.transform(self.X)
  
      seed = np.random.RandomState(1234)
      sdml = SDML_Supervised(
          n_constraints=1500,
          balance_param=1e-5,
          prior="identity",
          random_state=seed,
      )
      res_2 = sdml.fit_transform(self.X, self.y)
  
      assert_array_almost_equal(res_1, res_2)
  
file_path: metric-learn/test/test_fit_transform.py
imports: import unittest
  import numpy
  from sklearn.datasets import load_iris
  from numpy.testing import assert_array_almost_equal
  from metric_learn import LMNN, NCA, LFDA, Covariance, MLKR, LSML_Supervised, ITML_Supervised, SDML_Supervised, RCA_Supervised, MMC_Supervised
label_desc: Use image node_id 6 for calling the TestFitTransform obj's underlying member method code with example usage: obj.test_sdml_supervised() without return types